I will design and build ai mlops pipelines and ml microservices

Are your AI models running slow, crashing under heavy traffic, or burning through your cloud budget?---Most data science teams can build great models, but scaling them for production is a completely different challenge. If your model is tied to your main application monolith, a traffic spike can crash your entire business system.

I will decouple your machine learning models into scalable, production-grade microservices using Docker and Kubernetes so you can cut infrastructure costs and unlock blazing-fast inference speeds.

What I Solve For You:

• Production Deployment: I convert raw Python/ML scripts into production-ready, containerized API endpoints.
• GPU Cost Optimization: I separate your web traffic from your model inference, ensuring you only pay for expensive cloud compute when your AI is actually running.
• Zero-Downtime Infrastructure: I build resilient, automated setups that keep your core app running even if a model pod experiences an error.
• Expert Debugging: I jump into existing clusters to resolve container out-of-memory errors, broken pipelines, and environment mismatches.